An approach to rapid optimization of antennas using the shape-preserving response-prediction (SPRP) technique and coarsediscretization electromagnetic (EM) simulations (as a low-fidelity model) is presented. SPRP allows us to estimate the response of the high-fidelity EM antenna model, e.g., its reflection coefficient versus frequency, using the properly selected set of so-called characteristic points of the low-fidelity model...

Computer simulation models are ubiquitous in modern engineering design. In many cases, they are the only way to evaluate a given design with sufficient fidelity. Unfortunately, an added computa-tional expense is associated with higher fidelity models. Moreover, the systems being considered are often highly nonlinear and may feature a large number of designable parameters. Therefore, it may be impractical to solve the design problem...

Artykuł prezentuje metodologię dokładnego modelowania struktur mikrofalowych. Jest to zmodyfikowana wersja techniki opartej na procedurze przewidywania odpowiedzi z zachowaniem kształtu (shape-preserving response prediction, SPRP), która oszacowuje odpowiedź struktury mikrofalowej otrzymanej poprzez kosztowną obliczeniowo symulację elektromagnetyczną za pomocą taniego obliczeniowo modelu tejże struktury. Modyfikacja polega na wykorzystaniu...

A brief review of some recent variable-fidelity aerodynamic shape optimization methods is presented.We discuss three techniques that—by exploiting information embedded in low-fidelity computationalfluid dynamics (CFD) models—are able to yield a satisfactory design at a low computational cost, usu-ally corresponding to a few evaluations of the original, high-fidelity CFD model to be optimized. Thespecific techniques considered here...

Aerodynamic shape optimization (ASO) involves computational fluid dynamics (CFD)-based search for an optimal aerodynamic shape such as airfoils and wings. Gradient-based optimization (GBO) with adjoints can be used efficiently to solve ASO problems with many design variables, but problems with many constraints can still be challenging. The recently created efficient global optimization algorithm with neural network (NN)-based prediction...